Integrating clinical, genomic, metabolomic and dietary data through machine learning to improve our understanding of their influences on blood pressure regulation / P. Louca, T. Tran, C. du Toit, P. Christofidou, T. Spector, M. Mangino, K. Suhre, S. Padmanabhan, C. Menni. - In: JOURNAL OF HUMAN HYPERTENSION. - ISSN 0950-9240. - 36:Suppl. 1(2022), pp. 1-2. (Intervento presentato al convegno Annual Scientific Meeting of the British and Irish Hypertension Society (BIHS) nel 2022).
Integrating clinical, genomic, metabolomic and dietary data through machine learning to improve our understanding of their influences on blood pressure regulation
C. Menni
Ultimo
2022
File in questo prodotto:
File | Dimensione | Formato | |
---|---|---|---|
s41371-022-00734-5.pdf
accesso riservato
Tipologia:
Publisher's version/PDF
Dimensione
799.21 kB
Formato
Adobe PDF
|
799.21 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.